Aquaporins Respond to Chilling in the Phloem by Altering Protein and mRNA Expression
Bibliographic record
Abstract
Previous experiments using heat exchangers (liquid cooled blocks) to chill a portion of plant stem have shown a transient stoppage in phloem translocation and an increase in measured phloem pressure. Although a chilled-induced stoppage of phloem transport has been known for over 100 years, the mechanism of this phenomenon is still poorly understood. Recently, work has highlighted that aquaporins occur within the plasma membrane of the sieve tubes along the entire source-to-sink pathway, and that isoforms of these water channel proteins may change dynamically. Aquaporins show regulatory roles in controlling tissue and cellular water status in response to environmental hardships. Thus, we tested if protein localization and mRNA transcript abundance changes occur in response to chilling in balsam poplar (Populus balsamifera) using immunohistochemistry and qrtPCR. The results of the immunolocalization experiments show that the labeling intensity of the sieve elements treated for only 2 min of chill time significantly increased for PIP2. After 10 min of chilling, this signal declined significantly to lower than that of the pre-chilled sieve elements. Overall, the abundance of mRNA transcript increased for the tested PIP2s following cold application. We discuss the implication that aquaporins are responsible for the alleviation of sieve tube pressure and the resumption of flow following a cold-induced blockage event.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".